Preprints
https://doi.org/10.5194/tc-2022-98
https://doi.org/10.5194/tc-2022-98
 
24 May 2022
24 May 2022
Status: a revised version of this preprint is currently under review for the journal TC.

Monitoring Arctic thin ice: A comparison between Cryosat-2 SAR altimetry data and MODIS thermal-infrared imagery

Felix L. Müller1, Stephan Paul2,1, Stefan Hendricks2, and Denise Dettmering1 Felix L. Müller et al.
  • 1Technical University of Munich, Germany; TUM School of Engineering and Design, Department of Aerospace & Geodesy, Deutsches Geodätisches Forschungsinstitut (DGFI-TUM)
  • 2Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven, Germany

Abstract. Areas of thin sea ice in the polar regions are not only experiencing the highest rate of sea-ice production but are, therefore, also important hot spots for ocean ventilation as well as heat and moisture exchange between the ocean and the atmosphere. Through co-location of (1) Moderate Resolution Imaging Spectroradiometer (MODIS) derived thin-ice thickness estimates with (2) an unsupervised waveform classification (UWC) approach and (3) Sentinel-1 A/B SAR reference data, thin-ice based waveform shapes are identified, referenced, and discussed with regard to a manifold of waveform shape parameters. Here, a strong linear dependency is found that shows the possibility to either develop simple correction terms for altimeter ranges over thin ice or to directly adjust current retracker algorithms specifically to very thin sea ice. This highlights the potential of CryoSat-2-based SAR altimetry to reliably discriminate between thick sea ice, open-water leads, as well as thin-ice occurrences within recently refrozen leads or mere areas of thin sea ice. Furthermore, a comparison to the ESA Climate Change Initiative's (CCI) surface-type classification reveals that the newly found thin-ice related waveforms are divided up between almost equally between 'unknown' (46.3 %) and lead-type (53.4 %) classifications. Overall, the UWC results in far fewer 'unknown' classifications (1.4 % to 38.7 %). Thus, UWC provides more usable information for sea-ice freeboard and thickness retrieval while UWC at the same time reduces range biases from thin-ice waveforms processed as regular sea ice in the CCI classification.

Felix L. Müller et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on tc-2022-98', Anonymous Referee #1, 04 Jul 2022
    • AC1: 'Reply on RC1', Felix L. Müller, 20 Oct 2022
    • AC4: 'Reply on RC1', Felix L. Müller, 20 Oct 2022
  • RC2: 'Comment on tc-2022-98', Anonymous Referee #2, 13 Sep 2022
    • AC2: 'Reply on RC2', Felix L. Müller, 20 Oct 2022
    • AC3: 'Reply on RC2', Felix L. Müller, 20 Oct 2022

Felix L. Müller et al.

Felix L. Müller et al.

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Short summary
Thinning sea ice has significant impacts on the energy exchange between the atmosphere and the ocean. In this study we present visual and quantitative comparisons, of thin ice detections obtained from classified Cryosat-2 radar reflections and thin-ice thickness estimates derived from MODIS thermal-infrared imagery. In addition to good comparability, the results of the study indicate the potential for a deeper understanding of sea ice in the polar seas and improved processing of altimeter data.